APOBEC2 safeguards skeletal muscle cell fate through binding chromatin and regulating transcription of non-muscle genes during myoblast differentiation
Bibliographic record
Abstract
The apolipoprotein B messenger RNA editing enzyme, catalytic polypeptide (APOBEC) family is composed of nucleic acid editors with roles ranging from antibody diversification to RNA editing. APOBEC2, a member of this family with an evolutionarily conserved nucleic acid-binding cytidine deaminase domain, has neither an established substrate nor function. Using a cellular model of muscle differentiation where APOBEC2 is inducibly expressed, we confirmed that APOBEC2 does not have the attributed molecular functions of the APOBEC family, such as RNA editing, DNA demethylation, and DNA mutation. Instead, we found that during muscle differentiation APOBEC2 occupied a specific motif within promoter regions; its removal from those regions resulted in transcriptional changes. Mechanistically, these changes reflect the direct interaction of APOBEC2 with histone deacetylase (HDAC) transcriptional corepressor complexes. We also found that APOBEC2 could bind DNA directly, in a sequence-specific fashion, suggesting that it functions as a recruiter of HDAC to specific genes whose promoters it occupies. These genes are normally suppressed during muscle cell differentiation, and their suppression may contribute to the safeguarding of muscle cell fate. Altogether, our results reveal a unique role for APOBEC2 within the APOBEC family.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".